Yazar "Vaheddoost, Babak" seçeneğine göre listele
Listeleniyor 1 - 20 / 61
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe A Case Study for Determination of the Best Underground Dam Sites, Bursa Province, Turkey(Wiley, 2024) Aras, Egemen; Boz, Burak; Vaheddoost, Babak; Yilmaz, DamlaWater constitutes an indispensable resource vital for sustaining life. In this context, groundwater stands out as a paramount global water source. Throughout history, underground dams (UGDs) have been employed to augment the storage capacity of local aquifers. This study employs a multistep elimination approach to identify optimal locations for constructing UGDs in the Bursa district, Turkey. Initially, the Digital Elevation Model (DEM) is utilized to pinpoint the potential construction sites at the watershed scale. Criteria such as suitable topographic slope range, proximity to the transport infrastructures, presence of natural or artificial reservoirs, distance to active or inactive faults, proximity to the urban and rural settlements, location of the irrigation zones, geological conditions, distance to the consumption hubs, thickness of alluvium layer, and the groundwater depth are used to establish the buffer zones for exclusion of potential sites. Then, storage volume in the proposed sites is determined, and formal requests from the local communities are taken into consideration for determining the best UGD sites. The study concludes that five UGDs for irrigation and one for drinking water purposes could be recommended for further implementation. The potential locations of underground dams have been determined in the city of Bursa, which has a very high underground water potential. Twelve different criteria were applied to determine the project location. After all criteria were applied, six different underground dam locations were determined depending on the city's water and irrigation needs. imageÖğe A CMIP6-based drought assessment over Küçük Menderes Basin,Türkiye(Springer Wien, 2025) Rotbeei, Farzad; Nuri Balov, Mustafa; Safari, Mir Jafar Sadegh; Vaheddoost, BabakDroughts are the phenomenon of which their magnitude and frequency are forecasted to escalate over time primarily due to the impacts of climate change and global warming. Hence, the potential consequences of the expected drought events are of the great importance in performing effective adaptation and regional mitigation strategies. The objective of the current study is to explore the consequences of climate change on the future droughts in K & uuml;& ccedil;& uuml;k Menderes Basin in western T & uuml;rkiye. This objective will be addressed by examining the outputs of four General Circulation Models (GCMs) incorporated within Phase 6 of the Coupled Model Inter-comparison Project (CMIP6), with particular emphasis on two contrasting emission trajectories: SSP2-4.5 and SSP5-8.5. The daily precipitation and temperature projections are then utilized in determination of the so-called Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) drought indices with consideration to 2015-2039 as near future, 2040-2069 as mid-term future, and 2070-2099 as late future time frames. According to projections based on the SSP2-4.5 and SSP5-8.5 scenarios, the number of dry months is anticipated to escalate by approximately 26.12% and 39.80%, respectively, toward the end of the twenty-first century (2070-2099), in contrast to the reference period (1985-2014). Results of the current study provide valuable insights for developing adaptation strategies to address future consequences of drought events in the K & uuml;& ccedil;& uuml;k Menderes Basin amid evolving climate conditions.Öğe A Joint Evaluation of Streamflow Drought and Standard Precipitation Indices in Aegean Region, Turkey(Springer Basel Ag, 2023) Gulmez, Ayse; Mersin, Denizhan; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Tayfur, GokmenWater is an invaluable substance that ensures the life cycle and causes hydrologic events worldwide. Water deficit, also known as drought, is a naturally occurring disaster that affects the hydrometeorologic and/or climatic responses in time and space. In this study, the meteorologic and hydrologic droughts in Buyuk Menderes, Kucuk Menderes, and Gediz basins in Turkey are investigated. The streamflow drought index (SDI) and standard precipitation index (SPI) are used considering different time windows. To achieve this, the monthly streamflow at Cicekli-Nif, Besdegirmenler-Dandalas, Bebekler-Rahmanlar, and Kocarli-Koprubasi hydrometric stations together with monthly precipitation at 14 meteorologic stations during 1973-2020 (47 years) are used. The SDI and SPI with 1, 3, 6, and 12 months moving average are then used to express the association between the meteorologic and hydrologic droughts in the basin. Results showed that the SDI depicts no abnormal situations, while the SPI rates in the 1980s and 2010s indicated severe droughts. It was concluded that the inner parts of the basins are prone to frequent droughts, and there is a concordance between SPI and SDI patterns at the basin level. However, minor discrepancies between SPI and SDI do exist and probably originated from temporal delays and water abstraction.Öğe A LABORATORY SCALE INVESTIGATION OF MANNING ROUGHNESS COEFFICIENT IN OPEN CHANNEL BED WITH DIFFERENT GRAIN SIZE AND SLOPES(2023) Yılmaz, Damla; Aras, Egemen; Vaheddoost, BabakEfforts for getting the maximum efficiency from the existing water resources and to implement new projects are getting more attention these days. Determining the flow resistance for the project design and control process in open channels requires sophisticated applications. It is usually essential to be aware of the characteristics of the channel and flow to determine the hydraulic roughness, which represents the resistance of the flow. Hence, empirical calculation and evaluation of the hydraulic roughness will support future design and planning processes. In this study, four different particle sizes (d50= 28mm, 17.5mm, 4mm, and 1.75mm) that were fixed on blocks were used. These particle sizes were then used as the bed covering together with, three different horizontal bed slopes, and flow rates in the experiments to determine the associated Manning roughness, n. During the experiment, Froude number values were examined and it was determined that, in 32 experiments the flow regime can be considered as subcritical. Alternatively, the Lotter method was used to confirm the roughness values obtained by the Manning equation. It was concluded that the roughness values obtained by the selected methods have good concordance with each other.Öğe A Laboratory Study on the Design and Performance Evaluation of Pitot-Tube(2023) Eski, Yasemin; Vaheddoost, Babak; Yılmaz, DamlaDue to the increasing demand for water resources worldwide, this commodity and its spatial and temporal properties are of the interest for decision makers and scientists. On the other hand, the accuracy in detecting the physical characteristics of the water flow such as velocity is among the most important aspects of the hydraulic studies. The pitot tube, which is not widely used in the open channel hydraulic practices, is one of the equipment used for determination of the flow velocity. In this study, we have addressed the design, fabrication, and laboratory experiments related to a pitot tube to investigate its applicability for open channel experiments. A 3D-printed pitot-tube is designed and used in a set of experiments carried out in an open channel, with different flow rates (three experiments). As a result, the relative error rates were interpreted by comparing the velocity rates obtained with the help of the water level difference in the differential manometer (Vm) and the velocity rates obtained from the flow continuity equation in the open channel (Vo). Results indicated a 50% bias, while the scatter analysis showed that the associated deviations match a linear equation and once used in the interpretation of the results, the linear transformation reveals a 3% bias in the experiments.Öğe A multi-step strategy for enhancing the rainfall-runoff modeling: combination of lumped and artificial intelligence-based hydrological models(Springer, 2025) Mohammadi, Babak; Safari, Mir Jafar Sadegh; Vaheddoost, Babak; Yilmaz, Mustafa UtkuAccurate rainfall-runoff (RR) modeling holds significant importance in environmental management, playing a central role in understanding the dynamics of water cycle. In this respect, the precision in the determination of RR is crucial for mitigating the adverse effects of both water scarcity and excessive runoff, ensuring the sustainable management of ecosystems and water resources. As a primary hydrological variable, runoff engages in direct interactions with other hydrological variables. Due to the complexity of the RR process, two primary approaches are commonly used in modeling, namely conceptual (lumped) models and artificial intelligence (AI) models. Conceptual approaches are based on hydrological processes and use a larger number of hydrological variables, yet they often exhibit lower performance compared to AI models. In contrast, AI models rely on fewer parameters and lack physical interpretability, but demonstrate high performance. This study merges the advantages of both lumped and AI techniques to develop an advanced RR model. Hence, the applicability of several lumped and AI-based models in estimating the streamflow rates with the help of basic meteorological variables is investigated. The lumped hydrological models, namely the Modello Idrologico SemiDistribuito in continuo (MISD), Identification of Unit Hydrographs and Component Flows from Rainfall, Evaporation, and Streamflow (IHACRES), and G & eacute;nie Rural & agrave; 4 param & egrave;tres Journalier (GR4J), are employed in conjunction with AI algorithms as Radial Basis Function (RBF) neural networks, Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP). An ensemble of conceptual models (MISD, IHACRES, and GR4J) and three AI models (MLP, RBF, and ANFIS) with various lag times are considered as effective variables, where Support Vector Machine (SVM) was utilized as a feature selection method with five different kernels in determining the best inputs. Afterward, the SVM-ANFIS model, as the best model, is hybridized with Ant Colony Optimization (ACO) to develop the SVM-ANFIS-ACO model. It is found that the coupling of lumped and AI methodologies considerably enhanced the accuracy of the RR models; and SVM-ANFIS-ACO outperformed other models in streamflow computation.Öğe A Spatiotemporal Classification of the Peruvian Precipitations Between 1990 and 2015(Springer Basel Ag, 2020) Vaheddoost, BabakPrecipitation and its variations have great importance in water resource management and sustainable development. In this study, the Peruvian precipitations between January 1990 to October 2015, were used. The precipitations were classified under spatial, temporal, and spatiotemporal classes. For this aim, properties of the precipitation time series including the monthly mean, monthly standard deviation, and principal components at monthly and annual scale were evaluated. Results were projected on a map using the Kriging method. Later, the double mass curves of the monthly precipitation time series were used to classify the temporal changes in the precipitations. Thereafter, the Spearman rank-order correlation was used to evaluate the spatiotemporal changes in monthly and annual precipitation time series by projected t-values on the Peruvian map. Finally, precipitations time series were plotted against Koppen-Geiger climate class of each station and several large scale oscillations namely North Atlantic Oscillation (NAO), El Nino/Southern Oscillation (ENSO), Atlantic Multi-decadal Oscillation (AMO), and Pacific Decadal Oscillation (PDO) simultaneously. It was concluded that there are at least three major climatic regions in the country. Spatial classes, depicts that the Andes Ranges is a major role player in the climate of the country while the ENSO and PDO are the main drivers of the precipitation extremes. Results also indicated to an ascending changes in the amount of precipitation from west to east, while a descending changes were observed at Amazon forest near San Ramon.Öğe A spatiotemporal teleconnection study between Peruvian precipitation and oceanic oscillations(Pergamon-Elsevier Science Ltd, 2020) Mohammadi, Babak; Vaheddoost, Babak; Mehr, Ali DanandehLarge-scale oceanic oscillations and their teleconnections with meteorological events are of great importance in macro-scale climatic studies. In this regard, this study investigates the spatiotemporal teleconnections between four oceanic oscillations, namely North Atlantic Oscillation (NAO), El Nino/Southern Oscillation (ENSO), Atlantic Multi-Decadal Oscillation (AMO), and Pacific Decadal Oscillation (PDO), against Peruvian precipitation patterns during the past 25 years (i.e., 1990-2015). For this purpose, variation in the precipitation pattern at monthly and annual scales as well as the Standardized Precipitation Index (SPI) time series at 1-, 3-, 12-, and 48-month time scales were evaluated at 10 meteorology stations across Peru. Pearson's correlation coefficient and mutual information between the oceanic oscillations and precipitation-born signals were calculated and spatially interpolated using the Kriging method. The results indicated the presence of three major climatic regions in the country. The NAO has the largest correlation with the monthly precipitation. However, the ENSO was found as the main climate driver of extremely wet and extremely dry conditions in the country. The results also demonstrated that the PDO has a higher impact on the annual precipitation pattern, particularly in the southern and eastern parts of the country.Öğe A Statistical Assessment of Drinking Water Quality: A Case Study of Doburca Treatment Plant, Bursa(2024) Yılmaz, Damla; Aras, Egemen; Vaheddoost, BabakIn order to provide and maintain urban health standards, assessing the quality of drinking water is an essential step. As a result of different pollutant factors (climate, heavy metals, vegetation, human activities, etc.), it is inevitable that the quality of water resources decreases day by day. In this study, the data of 21 water samples taken between January 2021 and June 2021 from the water drinking facility providing drinking water to Bursa were examined. Firstly, the strength and direction of the relationship between 10 different parameters (electrical conductivity (EC), copper (Cu), nickel (Ni), nitrate (?NO?_3^-), arsenic (As), iron (Fe), total dissolved substances (TDS), total alkalinity (TA), total hardness (TH) and dissolved oxygen (DO)) were evaluated with the help of relation analysis, water quality index, and polynomial curve fitting. The relationship of the parameters that do not have a linear correlation was also interpreted and finally, as a result of using the weighted arithmetic water quality index (WAWQI), it was determined that the potability of the water quality in the allocated water reservoir was at the 'excellent' level and fulfills the requirements.Öğe A stochastic approach for the assessment of suspended sediment concentration at the Upper Rhone River basin, Switzerland(Springer, 2022) Vaheddoost, Babak; Vazifehkhah, Saeed; Safari, Mir Jafar SadeghThis study addresses the link between suspended sediment concentration, precipitation, streamflow, and direct runoff components. This is important since suspended sediment concentration in the streamflow has invaluable importance in the management of the river basin. For this, the daily streamflow time series in five consecutive stations at Upper Rhone River Basin, a relatively large basin in the Alpine region of Switzerland, daily precipitation at one station, and the twice a week suspended sediment concentration records at the most downstream station between January 1981 and October 2020 are used. Initially, the base flow and the direct runoff associated with streamflow time series are obtained using the sliding interval method. Elasticity analyses between streamflow and suspended sediment concentration together with correlation, autocorrelation, partial autocorrelation, stationarity, and homogeneity are examined by the Augmented Dickey-Fuller and Pettitt's tests, respectively. Then, various stochastic scenarios are generated using the autoregressive moving average exogenous method (ARMAX). It is concluded that the precipitation and direct runoff have fewer effects on the suspended sediment concentration at downstream of the river. Hence, the cumulative effect of the glacier or snowmelt and channel erosion may exceed the effect of rain blown washouts on the suspended sediment concentration at the Port du Scex station. It is found that the ARMAX model results are satisfactory and can be suggested for further application.Öğe A study of the relationship between GRACE-TWSA and large-scale atmospheric-oceanic patterns(Taylor & Francis Ltd, 2025) Vaheddoost, Babak; Mohammadi, BabakThis study aims to investigate the connections between changes in the Total Water Storage Anomaly (TWSA) associated with 12 continental/subcontinental regions derived from the Gravity Recovery and Climate Experiment (GRACE) satellite and 25 different Large-Scale Climate Oscillation Indices (LSCOI). Initially, correlation analyses were performed and then the principal component analyses together with wavelet coherent transform were employed in the analyses. The results explain over 50% of TWSA variability, with the Pacific and Indian Oceans exerting strong influence. While Southern Hemisphere regions display consistent long-term relationships with LSCOI patterns, the Northern Hemisphere exhibits more complex dynamics, including trade-offs between leading and lagging effects and in-phase versus anti-phase states. Random Forest and M5 Tree models were then applied using high-correlation LSCOIs as predictors for regional TWSAs. Results of models confirmed the robustness of the identified teleconnections and demonstrated the potential for predicting regional water storage anomalies using climate oscillation indices.Öğe Application of hybrid ANN-whale optimization model in evaluation of the field capacity and the permanent wilting point of the soils(Springer Heidelberg, 2020) Vaheddoost, Babak; Guan, Yiqing; Mohammadi, BabakField capacity (FC) and permanent wilting point (PWP) are two important properties of the soil when the soil moisture is concerned. Since the determination of these parameters is expensive and time-consuming, this study aims to develop and evaluate a new hybrid of artificial neural network model coupled with a whale optimization algorithm (ANN-WOA) as a meta-heuristic optimization tool in defining the FC and the PWP at the basin scale. The simulated results were also compared with other core optimization models of ANN and multilinear regression (MLR). For this aim, a set of 217 soil samples were taken from different regions located across the West and East Azerbaijan provinces in Iran, partially covering four important basins of Lake Urmia, Caspian Sea, Persian Gulf-Oman Sea, and Central-Basin of Iran. Taken samples included portion of clay, sand, and silt together with organic matter, which were used as independent variables to define the FC and the PWP. A 80-20 portion of the randomly selected independent and dependent variable sets were used in calibration and validation of the predefined models. The most accurate predictions for the FC and PWP at the selected stations were obtained by the hybrid ANN-WOA models, and evaluation criteria at the validation phases were obtained as 2.87%, 0.92, and 2.11% respectively for RMSE, R-2, and RRMSE for the FC, and 1.78%, 0.92, and 10.02% respectively for RMSE, R-2, and RRMSE for the PWP. It is concluded that the organic matter is the most important variable in prediction of FC and PWP, while the proposed ANN-WOA model is an efficient approach in defining the FC and the PWP at the basin scale.Öğe Application of Signal Processing in Tracking Meteorological Drought in a Mountainous Region(Birkhauser, 2021) Vaheddoost, Babak; Safari M.J.S.This study addresses the application of signal processing in the evaluation of meteorological drought associated with monthly precipitation time series. Several drought indices and a Haar wavelet decomposition (WD) with ten components are implemented in the evaluation of the monthly precipitation of a mountainous region called Mount Uludag in Turkey. Monthly precipitation time series in three meteorological stations at the summit and foothills are used. The Standardized Precipitation Index (SPI) is used at monthly, annual, and 12- and 48-month moving average time frames as the benchmark to investigate the drought patterns. The results obtained by the WD and SPI are then confirmed using the Z-score index (ZSI) at monthly and annual scales, together with the modified China Z-index (MCZI) and rainfall anomaly index (RAI) at a monthly scale. Changes in the moments of the distribution, correlation analysis, mutual information, and power spectrum are applied to investigate the nature of the relationship between the sequences of precipitation events in time and space. The temporal correlation analysis, together with the mutual information, showed that the system has a short-term memory with strong seasonality. Similarly, the power spectra depicted major seasonality at 1, 3, 5, 6, 12, 22, and 60 months in the precipitation time series. It is concluded that the recent drought events have an infrequent nature, which altered the sinusoidal patterns of the large-scale events. The SPI-48 and the WD showed that declines are strongly related to the large-scale cycles, but the decline patterns are more related to the station located at the mountain summit.Öğe Assessment of Drought in Izmir District Using Standardized Precipitation Index(Springer Nature, 2025) Mersin, Denizhan; Gulmez, Ayse; Safari, Mir Jafar Sadegh; Vaheddoost, Babak; Tayfur, GökmenOne of the main issues with agro-food and socio-economical security in the world is droughts. Regardless of cause or effect, the ever-changing climate is placing increasing strain on water resources pushing supply to its limits. Izmir, a growing city in Turkey, is endowed with variety of water resources, such as lakes, rivers, seashores, and groundwater reserves. Therefore, it is crucial for the planning and development of the area to examine past and foreseeable drought occurrences and their possible impact on water resources. In this regard, the study’s goal is to assess historical droughts in Izmir District. Data from three meteorological stations in Küçük Menderes basin, collected between 1973 and 2020, are utilized in this study. To establish the validity of the posterior drought analysis, the consistency and trend in the time series are first examined using the double mass curve, run test, and linear trend analysis. The next step is to assess the historical deficit related to meteorological, agricultural, and hydrological droughts using the SPI and moving mean (MA) operator. The temporal analysis of SPI reveals distinct drought patterns across the stations, with multiple moderate to extreme droughts occurring particularly between 1998 and 2010, highlighting significant spatial and temporal variability in drought severity and frequency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Öğe Assessment of water demand reliability using SWAT and RIBASIM models with respect to climate change and operational water projects(Elsevier, 2022) Fathian, Farshad; Ahmadzadeh, Hojat; Mansouri, Bahareh; Vaheddoost, BabakReliability assessment in the allocation of water resources under the changing climate condition has invaluable importance in planning the water demand at the basin scale. This study details an integrated framework for evaluation of the reliability between water supply and demand under climate change scenarios in the Zarrineh Rood River basin in the northwest of Iran. Initially, recorded climatic data in six synoptic stations are downscaled and projected for the period 2020-2040 based on the 14 GCMs using the LARS-WG method. Afterwards, the SWAT model is used to simulate the basin hydrology with consideration to the baseline and future climate periods at six hydrometric stations. Finally, the available water is allocated using the RIBASIM model based on the current supply-demand chain and predefined governmental water allocation rules for different sectors. Results showed that under climate change, the total runoff of the basin and the entrance catchments to the Zarrineh Rood River dam would decrease about 8% and 28%, respectively. The reliability of the water supply for joint drinkingindustrial and agricultural demands would also decrease from 96.4% to 93.4%, and 90.2-89.5%, respectively. As such, the average annual streamflow from the Zarrineh Rood River ending to Lake Urmia will reduce by 10% if the operational water projects remain active.Öğe Comparability Analyses of Three Meteorological Drought Indices in Turkey(CRC Press, 2023) Vaheddoost, Babak; Safari, Mir Jafar SadeghThe following chapter investigates the role of precipitation in the evaluation of meteorological drought in a mountainous region. For this, Mount Uludag in Turkey was taken as the case of study. Three meteorological stations with quite long precipitation records were used. Monthly precipitation time series between January 1980 and October 2018 at the Keles and Osmangazi stations in the northern and southern hillsides, together with the Uludag station near the summit were used in the analysis. Afterward, the patterns in the data run, frequency changes, and temporal events related to the time series were evaluated using precipitation anomaly, z-index, autocorrelation, mutual information, and power spectrum. It was concluded that there is a strong seasonality in the data at every 6 and 12 months, whereas the temporal persistence is quite low and decays after the second time lag. In the next stage, three drought indices, namely the Standardized Precipitation Index (SPI), Deciles Index (DI), and percent of normal (PN) were calculated at monthly, seasonal, and annual scales for each station. Finally, a model based on the spatial, temporal, and spatiotemporal properties of the precipitation time series was developed using the multivariate adaptive regression splines (MARS) model. It was concluded that the spatial scenario is the best predictive model in the assessment of precipitation and drought, and the SPI is the best one-parameter meteorological drought index for use in drought studies. © 2024 Taylor & Francis Group, LLC.Öğe Conceptualization of the indirect link between climate variability and lake water level using conditional heteroscedasticity(Taylor and Francis Ltd., 2021) Fathian F.; Vaheddoost, BabakThis study investigates the indirect effect of large-scale climate oscillations and the corresponding teleconnection with lake water level (WL) oscillations. For this, the effect of the Southern Oscillation Index (SOI), and North Atlantic Oscillation (NAO) on the Lake Urmia WL during 1966–2016 is investigated using cross-correlation, cross-wavelet (XWT), wavelet-coherence (CWT), and nonlinear multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models. Based on the XWT and CWT analyses, a temporal phase of WL leading by the SOI and an anti-phase of WL-NAO linkage within 11 years is evident. The models also depict a long-term persistence and effectiveness of the conditional covariance on both SOI–WL and NAO–WL links. It is concluded that the SOI and NAO have no immediate impact on the WL while the magnitude of the impact is exacerbated after the year 2000; however, the establishment of the SOI–WL link is found to be more relevant than that of the NAO–WL link.Öğe Data Reconstruction for Groundwater Wells Proximal to Lakes: A Quantitative Assessment for Hydrological Data Imputation(Mdpi, 2025) Can, Murat; Vaheddoost, Babak; Safari, Mir Jafar SadeghThe reconstruction of missing groundwater level data is of great importance in hydrogeological and environmental studies. This study provides a comprehensive and sequential approach for the reconstruction of groundwater level data near Lake Uluabat in Bursa, Turkey. This study addresses missing data reconstruction for both past and future events using the Gradient Boosting Regression (GBR) model. The reconstruction process is evaluated through model calibration metrics and changes in the statistical properties of the observed and reconstructed time series. To achieve this goal, the groundwater time series from two observational wells and lake water levels during the January 2004 to September 2019 period are used. The lake water level, the definition of the four seasons via the application of three dummy variables, and time are used as inputs in the prediction of groundwater levels in observation wells. The optimal GBR model calibration is achieved by training the dataset selected based on data gaps in the time series, while test-past and test-future datasets are used for model validation. Afterward, the GBR models are used in reconstructing the missing data both in the pre- and post-training data sets, and the performance of the models are evaluated via the Nash-Sutcliffe efficiency (NSE), Root Mean Square Percentage Error (RMSPE) and Performance Index (PI). The statistical properties of the time series including the probability distribution, maxima, minima, quartiles (Q1-Q3), standard error (SE), coefficient of variation (CV), entropy (H), and error propagation are also measured. It was concluded that GBR provides a good base for missing data reconstruction (the best performance was as high as NSE: 0.99, RMSPE: 0.36, and PI: 1.002). In particular, the standard error and the entropy of the system in one case, respectively, experienced a 53% and 35% rise, which was found to be tolerable and negligible.Öğe Development of deep learning approaches for drought forecasting: a comparative study in a cold and semi-arid region(Springer Heidelberg, 2025) Gharehbaghi, Amin; Ghasemlounia, Redvan; Vaheddoost, Babak; Ahmadi, FarshadDrought is an intricate natural disaster that substantially menace the world. Its exact forecasting has a remarkable impact in several parts such as food production, business, industry, etc. In this study, in order to assess the drought procedure in Mahabad River basin, the temporal meteorological reconnaissance drought index (RDIMRB) in four diverse time scales including 3, 6, 9, and 12-month are computed using 576 monthly climatic datasets recorded from Sep 1974 to Aug 2022. To predict the time series RDIMRB, different standalone deep neural network (DNN) models including LSTM, GRU, Bi-directional LSTM (Bi-LSTM), and Bi-directional GRU (Bi-GRU) with the sequence-to-one regression module of forecasting (seq2one) are developed. For sake of this aim, the first 70% of data (395 months) and the last 30% of data (169 months) chronologically are used in the calibration and validation parts, respectively, to feed in the models development process. So as to achieve the most advantageous models' structure, a lot of scenarios are adopted by tuning the meant meta-parameters including NHU (number of hidden units), SAF (state activation function), and P-rate (learning dropout rate). According to the performance assessment criteria, total learnable parameters (TLP) criterion, and comparison plots, the Bi-GRU model is verified as the most satisfactory model, and best results are obtained in RDIMRB-12. It under the epitome meant meta-parameters achieved (i.e., NHU = 120, P-rate = 0.5, and softsign as the suitable SAF) results in the RMSE, MBE, NSE, PBIAS, and R2 of 0.17, 0.011, 0.92, -2.02%, and 0.86, respectively, nonetheless for the GRU model are gotten 0.64, 0.071, 0.23, 17.97%, and 0.65, respectively.Öğe Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients(Elsevier Ltd, 2021) Vaheddoost, Babak; Safari M.J.S.; Ilkhanipour Zeynali R.A novel method is suggested for the determination of flow discharge in vertical sluice gates with considerably small bias. First, in order to derive an equation for the discharge coefficient, energy-momentum equations are implemented to define the physical realization of the phenomenon. Afterward, the discharge coefficient is presented in terms of contraction and energy loss coefficients. Subsequently, discharge coefficient, contraction, and energy loss coefficients were determined through an implicit optimization technique on the data. Data analysis illustrated that there is a meaningful power relationship between the contraction and energy loss coefficients. Thereafter, dimensional analysis is performed and an explicit best-fit regression equation is developed for defining the energy loss coefficient. The obtained equations for contraction and energy loss coefficients were then used in the computation of the discharge coefficient and determination of the flow discharge in the vertical sluice gate. The performance of the developed approach is validated against the selected benchmarks existing in the literature.
